How a French SME in Smart Manufacturing Thrived in Turbulent Times with Predictores.ai's PIaaS

In today’s volatile market, where unpredictability can cripple even the most resilient businesses, one French SME in the B2B smart manufacturing sector turned uncertainty into opportunity. With the help of Predictores.ai and our Predictive Intelligence as a Service (PIaaS) solutions, this company not only secured its market position but also achieved significant growth. This success story highlights the power of Predictive Intelligence in navigating challenges and driving sustainable growth.

Company and Competitors: A Qualitative and Quantitative Overview

The company, TechInnov S.A. (* all names of company are changed), is a mid-sized enterprise based in Lyon, specializing in smart manufacturing solutions. With approximately 250 employees and annual revenues of €50 million, TechInnov serves a diverse B2B clientele across Europe, providing cutting-edge industrial automation and IoT-enabled manufacturing systems.

Competitors in the region include larger multinational corporations like Siemens and Schneider Electric, as well as other agile SMEs like Actemium and SPIE, who offer similar smart manufacturing solutions. Despite the intense competition, TechInnov has built a reputation for innovation and customized solutions tailored to the specific needs of its clients. However, the company faced mounting pressure from both global supply chain disruptions and the rapid technological advancements in the industry.

Challenge

The onset of global economic turbulence, exacerbated by the COVID-19 pandemic and geopolitical uncertainties, created significant challenges for TechInnov:

• Supply Chain Disruptions: With key suppliers in Asia facing shutdowns and logistical delays, TechInnov struggled to maintain production schedules, leading to missed deadlines and dissatisfied clients.

• Increased Competition: Larger competitors, with their vast resources, began aggressively targeting TechInnov’s client base with lower prices and advanced technology offerings.

• Market Uncertainty: The unpredictable market environment made it difficult for TechInnov to forecast demand accurately, leading to either overproduction or stockouts, both of which strained financial resources.

These challenges threatened TechInnov’s ability to compete and maintain its market position. The company needed a solution that could not only mitigate these risks but also provide a path to growth.

Solution: Implementing PIaaS with Predictores.ai

Recognizing the need for a transformative approach, TechInnov applied for being accepted for one of the limited Minimal Viable Product (MVP) research cooperations projects. TechInnov presented the pMVP project idea to the Executive Faculty Board and was approved for one MVP slot. The company partnered with Predictores.ai to implement our Predictive Intelligence as a Service (PIaaS). Our team worked closely with TechInnov to develop and deploy a customized predictive model tailored to their specific needs.

1. Supply Chain Optimization: We integrated real-time data from TechInnov’s supply chain, including supplier performance metrics, geopolitical developments, and logistical data, into our predictive model. This allowed TechInnov to anticipate disruptions and adjust procurement strategies accordingly.

2. Demand Forecasting: By multi-dimensionally analyzing historical sales data, market trends, and economic indicators, our PIaaS solution provided TechInnov with accurate demand forecasts. With the integrated Trust Analyzer® modul all defined and dynamically integrated information sources were evaluated in regard to objectivity, reliability and validity. With the result of the Trust Analyzer® the different sources are then dynamically weighted as part of the prediction algorithm so that sources with higher trust values are higher weighted in comparison to lower scoring sources. This enabled the company to optimize production schedules, reduce excess inventory, and avoid costly stockouts.

3. Competitive Positioning: Our solution included competitive intelligence features, allowing TechInnov to monitor the pricing strategies and technological advancements of their competitors. This enabled the company to adjust their offerings in real-time, maintaining a competitive edge in the market.

The Project Description

Based on the standard MVP process the different projects steps were realized within 8 months in accordance to the defined table - in time and on budget. At Predictores.ai, our MVP (Minimum Viable Product) process is designed to ensure a seamless transition from concept to deployment, providing robust and actionable Predictive Intelligence solutions. Here’s how our structured approach unfolds:

1. Target Definition: We start by clearly defining the objectives, ensuring alignment with your business goals.

2. Data Strategy: Next, we develop a comprehensive data strategy, integrating both available and external data sources.

3. Infrastructure & Data Structure: We then establish the necessary infrastructure and data structure to support the predictive model.

4. Alignment & Adjustment: Continuous alignment and adjustment ensure the solution is perfectly tailored to your needs.

5. MVP Development: Our PI Tech Stack is tested with initial data, allowing us to build a robust MVP that includes both backend and frontend components.

6. Piloting: We pilot the MVP with test data to fine-tune and validate the model.

7. Data Connection & Deployment: Upon successful testing, we connect all data sources and transition the MVP into a fully operational product.

8. Go Live: The final step is deployment, ensuring the Predictive Intelligence solution is live and delivering real value to your business.

This roadmap illustrates our commitment to delivering high-quality, scalable, and effective Predictive Intelligence solutions tailored to meet the unique needs of each client.

Realized Results, Lessons Learned, and ROI

The impact of implementing Predictores.ai’s PIaaS was immediate and profound:

1. Improved Supply Chain Resilience: TechInnov reduced supply chain disruptions by 35%, ensuring more consistent production schedules and improving customer satisfaction.

2. Enhanced Demand Accuracy: The demand forecasting model achieved an accuracy rate of 90%, leading to a 20% reduction in excess inventory and a 15% increase in on-time delivery.

3. Competitive Edge Maintained: By leveraging real-time competitive intelligence, TechInnov was able to retain key clients despite aggressive competition, resulting in a 10% increase in market share over 18 months.

4. Financial Impact and ROI: The implementation of PIaaS resulted in a 25% increase in annual revenue and a 30% reduction in operational costs. The ROI of the project was calculated at 300% within the first year, demonstrating the substantial value delivered by Predictive Intelligence.

Lessons Learned

• Data Integration is Key: Successful implementation of Predictive Intelligence requires seamless integration of diverse data sources. TechInnov’s ability to combine internal data such as available market and industry reports with hundres of pages through the Report Analyzer® modul without any halluzinations very well known by mainstream AI tools such as ChatGPT and others, with external factors like geopolitical developments was crucial to the project’s success.

• Agility in Strategy: In a rapidly changing market, the ability to adapt strategy in real-time is invaluable. The competitive intelligence component of our PIaaS allowed TechInnov to pivot quickly in response to competitor actions.

• Collaborative Implementation: The close collaboration between TechInnov’s team and Predictores.ai was essential in tailoring the PIaaS solution to meet the company’s unique challenges and goals.

Conclusion

In today’s uncertain market environment, Predictive Intelligence is not just a competitive advantage—it’s a necessity. For TechInnov S.A., partnering with Predictores.ai was a decisive move that enabled them to secure and grow their business, even in the face of significant challenges.

If your organization is looking to navigate the complexities of modern procurement and manufacturing with confidence, it’s time to explore what PIaaS from Predictores.ai can do for you. Contact us today to learn how we can help you achieve similar success.

Literature

• Chopra, S., & Sodhi, M. S. (2020). Managing Supply Chain Risk: Integrating with Risk Management. Journal of Supply Chain Management, 56(3), 73-88. Link

• Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research and Applications. International Journal of Production Economics, 176, 98-110. Link

• Mokhtar, M., & Soroka, A. (2021). Competitive Intelligence in the Manufacturing Sector: A Case Study Approach. Journal of Business Research, 123, 214-223. Link